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Table 1 Frequently used notations and descriptions

From: Improved cost-sensitive representation of data for solving the imbalanced big data classification problem

Notations

Descriptions

\(Z\)

The result of the feature extraction operation on X

\(X\)

Data matrix

\(Q\)

The mapping matrix

\(Y\)

Data label

\(n_{ + }\)

The number of positive class data

\(n_{ - }\)

The number of negative class data

\(b\)

The bias

\(\xi\)

The slack variable

n

The whole number of data points

\(\varepsilon\)

The reconstruction error

\(\omega\)

Denotes the coefficients of separating hyper-plane

\(v_{j}^{ - }\)

The empirical mean of the second order moment of the \(j{\text{th}}\) feature in the negative classes respectively

\(v_{j}^{ + }\)

The empirical mean of the second order moment of the \(j{\text{th}}\) feature in the positive classes respectively